Primary information processing of the vertebrate visual system can be considered as an image information processing system with multi-input-output. The input is a distribution of light intensity projected on the retin...Primary information processing of the vertebrate visual system can be considered as an image information processing system with multi-input-output. The input is a distribution of light intensity projected on the retina and the output represents the response of neural cells at a spatial location and time at a certain level in visual pathways. With the viewpoint of system analysis, properties of the system can be described by a weight展开更多
提出了基于Gabor小波和主元分析相结合的纹理图像分割算法。首先对纹理图像进行多通道滤波,获得了一系列滤波后的纹理图像。其次,借助于“能量测度”的概念,求解出各象素有效的纹理特征。为了进一步减少特征之间的信息冗余,降低聚类分...提出了基于Gabor小波和主元分析相结合的纹理图像分割算法。首先对纹理图像进行多通道滤波,获得了一系列滤波后的纹理图像。其次,借助于“能量测度”的概念,求解出各象素有效的纹理特征。为了进一步减少特征之间的信息冗余,降低聚类分析的计算负荷,采用主元分析(PCA)对所得的纹理特征进行降维。然后利用K M ean算法实现纹理图像的分类。最后针对所提算法,进行了仿真试验。展开更多
文摘Primary information processing of the vertebrate visual system can be considered as an image information processing system with multi-input-output. The input is a distribution of light intensity projected on the retina and the output represents the response of neural cells at a spatial location and time at a certain level in visual pathways. With the viewpoint of system analysis, properties of the system can be described by a weight
文摘提出了基于Gabor小波和主元分析相结合的纹理图像分割算法。首先对纹理图像进行多通道滤波,获得了一系列滤波后的纹理图像。其次,借助于“能量测度”的概念,求解出各象素有效的纹理特征。为了进一步减少特征之间的信息冗余,降低聚类分析的计算负荷,采用主元分析(PCA)对所得的纹理特征进行降维。然后利用K M ean算法实现纹理图像的分类。最后针对所提算法,进行了仿真试验。